José Antonio A. Antolínez

A Multimodal Wave Spectrum–Based Approach for Statistical Downscaling of Local Wave Climate

AbstractCharacterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g., Pacific Ocean). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, this study addresses these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in the statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “w...

A multiscale climate emulator for long-term morphodynamics (MUSCLE-morpho)

Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model.

Multiscale climate emulator of multimodal wave spectra: MUSCLE‐spectra

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications. This article is protected by copyright. All rights reserved.We thank Jorge Perez for the ESTELA code. A.R., J.A.A.A., and F.J.M. acknowledge the support of the Spanish ‘‘Ministerio de Economia y Competitividad’’ under grant BIA2014-59643-R. P.C. acknowledges the support of the Spanish ‘‘Ministerio de Economia y Competitividad’’ under grant BIA2015-70644-R. J.A.A.A. is indebted to the MEC (Ministerio de Educacion, Cultura y Deporte, Spain) for the funding provided in the FPU (Formacion del ProfesoradoUniversitario) studentship (BOE-A-2013-12235). This material is based upon work supported by the U.S. Geological Survey under grant/cooperative agreement G15AC00426. P.R. acknowledges the support of the National Oceanic and Atmospheric Administration Climate Program Office via award NA15OAR4310145. Support was provided from the US DOD Strategic Environmental Research and Development Program (SERDP Project RC-2644) through the NOAA National Centers for Environmental Information (NCEI). Atmospheric data from CFSR are available online at https://climatedataguide.ucar.edu/climatedata/climate-forecast-system-reanalysis-cfsr. Marine data from global reanalysis are lodge with the IHData center from IHCantabria and are available for research purposes upon request (contact: ihdata@ihcantabria.com).

Controls of Multimodal Wave Conditions in a Complex Coastal Setting

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Downscaling Changing Coastlines in a Changing Climate: The Hybrid Approach

This work was partially funded by the “U.S. National Science Foundation, Coupled Natural Human Systems Program.” J. A. A. Antolinez is indebted to the MEC (Ministerio de Educacion, Cultura y Deporte, Spain) for the funding provided in the FPU (Formacion del Profesorado Universitario) studentship (BOE-A-2013-12235). J. A. A. Antolinez and F. J. Mendez acknowledge the support of the Spanish “Ministerio de Economia y Competitividad” under grant BIA2014-59643-R.

A Climate Index Optimized for Longshore Sediment Transport Reveals Interannual and Multidecadal Littoral Cell Rotations

This work would not have been possible without funding from the NSF Graduate Research Fellowship Program (GRFP) through NSF grant DGE-1314109, the Coastal and Ocean Climate Applications (COCA) program through NOAA grant NA15OAR4310243, NOAA’s Regional Integrated Sciences and Assessments Program (RISA), under NOAA grant NA15OAR4310145, and the Spanish Ministerio de Educacion Cultura y Deporte FPU (Formacion del Profesorado Universitario) studentship BOE-A-2013-12235. Beach survey data collection undertaken on the Oregon coast was made possible by the Northwest Association of Networked Ocean Observing Systems (NANOOS) through NOAA grant NA16NOS0120019.